Direct on-line starting of Alternating Current (AC) induction motors causes harmful stress to upstream power supply systems and downstream mechanical systems. Solid-state soft starters providing voltage with reduced amplitude are used to ease that stress. AC induction motors are the workhorses in today's industries. AC induction motors have been widely used in different applications, for example, air compressors, centrifugal pumps, conveyors, cutting machinery, and so forth. These applications often may require soft starters to provide a smooth start for very diverse downstream mechanical systems. In current practice, systems have been providing operators with adjustable parameters such as starting voltage, starting current, deceleration time, and acceleration time via potentiometers, dip switches, or keypads. These systems also open the door to wrong settings that lead to unsatisfactory performance and the possibility of additional damage.
In current practice, voltage ramp algorithm and current limit algorithm are used to address variable load applications and constant load applications respectively. PID controllers are used in the algorithms for closed loop control. Because of nonlinearity of AC induction motors and uncertainty of their loads, conventional PID controllers alone are not capable of providing optimal control of AC induction motors. For instance, the standard voltage ramp algorithm currently used in industrial soft starters may not guarantee substantial reduction of torque and current peak values and may lose control at the end of soft start where the motor may become under-damped and power factor changes rapidly.
Unscheduled motor shutdowns are costly; hence it is of great interest that the motor controllers are also able to predict motor incipient faults. This invention presents an intelligent motor control algorithm that can provide not only soft start/soft stop but also prognosis on motor electrical, thermal, and mechanical faults.
Accordingly, an efficient and effective system and method is needed for regulating AC induction motors. In view of the foregoing, it is desirable to provide a system and method that minimizes operator involvement in adjusting soft starts. An intelligent soft start algorithm that would automatically adjust to different load characteristics is desired. A system and method may also prevent costly, unscheduled motor shutdowns.